Computational Perspectives on Social Phenomena in On-Line Networks

Опубликовано 17 августа 2016, 4:03

With an increasing amount of social interaction taking place in the digital domain, and often in public on-line settings, we are accumulating enormous amounts of data about phenomena that were once essentially invisible to us: the collective behavior and social interactions of hundreds of millions of people, recorded at unprecedented levels of scale and resolution. Analyzing this data computationally offers new insights into the design of on-line applications, as well as a new perspective on fundamental questions in the social sciences. We discuss how this perspective can be applied to questions involving network structure and the dynamics of interaction among individuals, with a particular focus on the ways in which evaluation, opinion, and in some cases polarization manifest themselves at large scales in the on-line domain